A life course perspective on gut microbiome aging and health in a non-human primate model

项目摘要 肠道微生物组一再与衰老的主要疾病有关，包括虚弱，骨质疏松症， 和糖尿病然而，经过十多年的寻找，仍然没有达成共识， 物种或分类学特征提供了成年人或老年人衰老的可靠标志。不同的人 拥有不同的微生物集合，其密度和动态从一个人到另一个人都有很大差异。 下一个.这种个性化的出现，部分是因为一个给定的微生物可能会执行不同的功能， 不同的人，甚至同一个人在不同的时间。这种可变性限制了 微生物组分类群（例如物种、门、生物多样性）来衡量健康和健康老龄化。克服这一 要跨越这一障碍，就需要改变策略，从分类数据转向反映直觉的数据类型 微生物组的功能能力，包括肠道中发现的微生物基因和代谢途径 微生物组的宏基因组开发健康老龄化的肠道微生物组标志物也需要前瞻性， 纵向人口研究。然而，我们缺乏跟踪纵向变化的前瞻性数据集 个体肠道微生物组功能和成年和老年的健康结果。 我们在这项提案中的目标是使用一个前瞻性的、完整的生命过程的非人灵长类动物模型来：（i） 确定整个生命过程中微生物组功能能力的变化;（ii）测试社会和 环境因素影响微生物组老化的性质和速度;（iii）测试分类功能关系如何 在不同的生命阶段发生变化;以及（iv）了解哪些微生物群特征预测身体/行为衰老， 全因死亡率我们的系统，经过充分研究的肯尼亚安博塞利狒狒种群， 人类行为和社会条件的复杂性优于其他动物模型。我们已经 在14年内从501个国家收集的17，277份粪便样本中分析了肠道微生物分类组成 狒狒这些数据揭示了个性化的微生物组动力学和衰老轨迹， 个人的社会和环境条件。我们建议将这一数据集再扩展10年， 包括总共800个个体，并分析12，000个样品中微生物组功能能力。通过识别 微生物群功能老化的驱动因素和模式，我们将确定旨在建立 并维持健康的衰老。我们的研究结果将有助于利用肠道微生物组的承诺来预测和 改善人类健康。

PROJECT SUMMARY The gut microbiome has repeatedly been linked to major diseases of aging, including frailty, osteoporosis, and diabetes. However, after more than a decade of searching, there is still no consensus on which microbial species or taxonomic features provide reliable hallmarks of aging in adults or the elderly. Different people harbor different collections of microbes with densities and dynamics that vary considerably from one person to the next. This personalization arises, in part, because a given microbe may perform different functions in different people, and even in the same person at different times. This variability constrains the utility of microbiome taxa (e.g. species, phyla, biodiversity) to measure health and healthy aging. Overcoming this hurdle requires a shift in strategy, away from taxonomic data and towards data types that reflect the gut microbiome’s functional capacities, including the microbial genes and metabolic pathways found in the gut microbiome’s metagenome. Developing gut microbiome markers of healthy aging will also require prospective, longitudinal population-based research. However, we lack prospective data sets that track longitudinal changes in individual gut microbiome function and health outcomes across adulthood and old age. Our objectives in this proposal are to use a prospective, full life course, nonhuman primate model to: (i) identify changes in the microbiome’s functional capacities across the life course; (ii) test how social and environmental factors affect the nature and pace of microbiome aging; (iii) test how taxa-function relationships change at different life stages; and (iv) learn which microbiome features predict physical/behavioral aging and all-cause mortality. Our system, the well-studied Amboseli baboon population in Kenya, captures the complexity of human behavioral and social conditions better than other animal models. We have already profiled gut microbial taxonomic composition in 17,277 fecal samples collected over 14 years from 501 baboons. These data reveal personalized microbiome dynamics and aging trajectories that are shaped by individual social and environmental conditions. We propose to expand this data set for 10 more years to include 800 total individuals and analyze microbiome functional capacity in 12,000 samples. By identifying drivers and patterns of microbiome functional aging, we will identify targets for interventions aimed at building and sustaining healthy aging. Our results will help harness the promise of the gut microbiome to predict and improve human health.